Suchergebnisse

BACKGROUND: Individual and environmental factors have been found to be related to cognitive function. However, few studies have examined the longitudinal effects of both individual and environmental factors over time. The purpose of this study was to examine the effects of individual and environmental factors over time on older people's cognitive function. METHODS: Nationally representative panel data from the Taiwan Longitudinal Survey on Aging 1999–2015 (n = 6349 persons, observations = 12,042) were used. City-level indicator data were sourced from the government. A multilevel mixed linear model analysis was conducted. RESULTS: Better cognitive function was significantly related to individuals' work, ethnicity, younger age, higher education level, better self-rated health, higher level of emotional support received, being more religious, higher economic satisfaction, and living in the cities with higher population densities. Education and social connectedness were protective factors over time. CONCLUSION: Socioeconomics and social connectedness are related to cognitive function. A more social integrated lifestyle and financially secure living is suggested in the policy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-02940-9.

The dominant approach to environmental policy endorsed by conservative and libertarian policy thinkers, so-called "free market environmentalism" (FME), is grounded in the recognition and protection of property rights in environmental resources. Despite this normative commitment to property rights, most self-described FME advocates adopt a utilitarian, welfare-maximization approach to climate change policy, arguing that the costs of mitigation measures could outweigh the costs of climate change itself. Yet even if anthropogenic climate change is decidedly less than catastrophic, human-induced climate change is likely to contribute to environmental changes that violate traditional conceptions of property rights. Viewed globally, the actions of some countries—primarily industrialized nations—are likely to increase environmental harms suffered by other countries—less developed nations that have not (as of yet) made any significant contribution to climate change. It may well be that aggregate human welfare would be maximized in a warmer, wealthier world, or that the gains from climate change will offset environmental losses. Yet such claims, even if demonstrated, would not address the normative concern that the consequences of anthropogenic global warming would infringe upon the rights of people in less-developed nations. As a consequence, this paper calls for a rethinking of FME approaches to climate change policy.

ABSTRACTGhana's pursuit of socio-economic growth has necessitated joining the information communication technology (ICT) revolution, thus increasing the consumption and obsolescence rate of electrical and electronic equipment (EEE) and the creation of what is popularly called e-waste. The absence of legislation governing its importation and disposal, combined with the dynamics of Accra's urban economy, including neo-liberal policies and lack of formal job opportunities, has triggered people's ingenuity to engage in novel occupations such as e-waste recycling. Though a lucrative strategy, it comes with a price for those involved: environmental health risks, a fact well articulated by a burgeoning literature. Nevertheless, little empirical evidence exists relating to this perceived relationship. Using questionnaires, FGDs and in-depth interviews, this study fills the lacuna. The findings reveal that the mean daily income of an e-waste worker is GH¢30, far above the daily minimum wage of GH¢4·48. Despite the positives, the findings also show that the environment and health can be compromised.

"How can each of us live Cooler Smarter? While the routine decisions that shape our days-- what to have for dinner, where to shop, how to get to work-- may seem small, collectively they have a big effect on global warming. But which changes in our lifestyles might make the biggest difference to the climate? This science-based guide shows you the most effective ways to cut your own global warming emissions by twenty percent or more, and explains why your individual contribution is so vital to addressing this global problem. Cooler Smarter is based on an in-depth, two-year study by the experts at The Union of Concerned Scientists. While other green guides suggest an array of tips, Cooler Smarter offers proven strategies to cut carbon, with chapters on transportation, home energy use, diet, personal consumption, as well as how best to influence your workplace, your community, and elected officials. The book explains how to make the biggest impact and when not to sweat the small stuff. It also turns many eco-myths on their head, like the importance of locally produced food or the superiority of all hybrid cars. The advice in Cooler Smarter can help save you money and live healthier. But its central purpose is to empower you, through low carbon-living, to confront one of society's greatest threats"--

Implemented by a joint initiative of ARL and DATAR (Délégation à l'Aménagement du Territoire et à l'Action Régionale) an international group of experts elaborated the Vision encompassing the shift from a sectoral, i.e. pure agricultural policy of today, to a territorial policy for rural regions to be implemented over a 25 year time horizon. This policy constitutes a desired vision for Europe's rural areas which requires: (1) appropriate institutions, (2) diversifying the economic activities in rural areas, and (3) integrating agricultural and rural policy. To achieve that shift to an integrated policy we need - new institutional frameworks, both on European and national levels, - effective instruments to guarantee the sustainable use of natural resources in agriculture, - the care for the rural population as a whole not only for farmers, - the improvement of quality products and production processes meeting the required environmental and animal welfare standards guaranteeing international competitiveness, - compatibility of the single European market for agricultural products with respect to prices and safety standards with commitments under the WTO, - a policy design and implementation at a decentralised level, and - a coordination of that policy at European and national levels for the benefit to implement the principles of solidarity and cohesion.

In the last decade, as many other European countries, the Italian Government adopted several reforms in order to increase the use of Renewable Energy Sources (RES). The liberalization of the electricity market that represents one of these reforms aims to reach environmental benefits from the substitution of fossil fuel with renewable sources. The Italian Green Certificate market was introduced in 2002 in order to accomplish this objective and represents a mechanism where a quota of renewable electricity is imposed to suppliers in proportion to their sales. The electricity industries are obliged to meet this condition by producing the quantity of renewable electricity by means of a change in their production process, otherwise they must buy a number of certificates corresponding to the quota. This mechanism changes the importance of the electricity industry first in promoting climate protection, then in terms of the impact on the economy as a whole. A policy aimed to develop the market of green certificates may lead to environmental improvement by switching the energy production process to renewable resources. But above all an increase in demand for green certificates, resulting from a reform on the quota of renewable electricity, can generate positive change in all components of the industrial production. For this purpose, the paper aims to quantify the economic impact of a reform on Green Certificate market for the Italian system by means of the Macro Multiplier (MM) approach. The analysis is performed through the Hybrid Input-Output (I-O) model that allows expressing the energy ows in physical terms (GWh) while all other ows are expressed in monetary terms (€). Moreover, through the singular value decomposition of the inverse matrix of the model, which reveals the set of key structures of the exogenous change of final demand, we identify the appropriate key structure able to obtain both the expected positive total output change and the increase of electricity production from RES.

Few social scientists have paid attention to how the press covers regulatory policy making in the United States. Those who have argue that the press does not cover regulatory policy with vigor. To assess this view, we compared what the Environmental Protection Agency did in one year with the coverage the agency received in two national newspapers in that same year. We find that the newspapers did not neglect the EPA. Although the newspapers certainly did not cover everything the agency did, they covered those regulatory actions that had the most direct impact on the public. The press gets out the message about regulatory actions that affect everyday life, shift policy in novel directions, and result in policy failure. Our findings suggest that scholars should pay more attention to the impact press coverage might have on the regulatory process.

This paper examines the technical, economic, and political factors that shaped the Kenyan photovoltaic (PV) market. Against a backdrop of initial economic growth and then price and policy fluctuation, the authors examine the evolution of the Kenyan PV market, its development, and what forces have helped or hindered the dissemination of PV technology. The paper also evaluates the mechanisms and methods of technology transfer, suggests several courses of action that can benefit current and potential PV users in Kenya, and examines the impact that PV has had in Kenya. (DÜI-Hff)

This study examines the spillover effects of foreign direct investment (FDI) on green technology progress rate (as measured by the green total factor productivity). The analysis utilizes two measures of FDI, labor-based FDI and capital-based FDI, and separately investigates four sets of industry classifications—high/low discharge regulation and high/low emission standard regulation. The results indicate that in the low discharge regulation and low emission standard regulation industry, labor-based FDI has a significant negative spillover effect, and capital-based FDI has a significant positive spillover effect. However, in the high-intensity environmental regulation industry, the negative influence of labor-based FDI is completely restrained, and capital-based FDI continues to play a significant positive green technological spillover effects. These findings have clear policy implications: the government should be gradually reducing the labor-based FDI inflow or increasing stringency of environmental regulation in order to reduce or eliminate the negative spillover effect of the labor-based FDI.

International audience ; Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. ; Les modèles bioéconomiques de ferme sont des outils pour évaluer ex-post ou anticiper ex-ante l'impact des changements des politiques et des technologies sur l'agriculture, l'économie et l'environnement. Récemment, différents BEFMs ont été développés, souvent dans un seul but ou localisation, mais aucun de ces modèles n'a été réutilisé plus tard à d'autres fins ou lieux. Le Farm System Simulator (FSSIM) fournit un cadre générique permettant l'application de BEFMs dans différentes situations et à diverses fins (estimation des fonctions d'offre, évaluations détaillées régionale ou par type de ferme…). FSSIM est conçu comme un cadre de modélisation intégré avec des composants qui représentent les objectifs des agriculteurs, le risque, le calibrage, les politiques publiques, les activités courantes, les activités alternatives, les différentes activités de production (par exemple, les cultures annuelles et pluriannuelles et l'élevage). Le caractère générique du modèle FSSIM est évalué selon cinq critères en examinant ses applications. FSSIM a été appliqué à diverses zones pédoclimatiques (critère 1) et à plusieurs types d'exploitations (critère 2) avec différentes spécialisations, intensités et tailles. Dans la plupart des applications FSSIM a été utilisé pour évaluer les effets des changements des politiques et dans deux applications pour évaluer l'impact des innovations technologiques (critère 3). Dans les différentes applications, plusieurs sources de données, niveau de détail (par exemple, le critère 4) et configurations du modèle ont été utilisés. FSSIM a été couplé à un modèle économique et à plusieurs modèles biophysiques (critère 5). Le modèle est disponible pour des applications à d'autres conditions et enjeux de la recherche, et il est ouvert à de nouveaux essais et à être étendue avec de nouveaux composants, indicateurs ou liens vers d'autres modèles.

International audience ; Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. ; Les modèles bioéconomiques de ferme sont des outils pour évaluer ex-post ou anticiper ex-ante l'impact des changements des politiques et des technologies sur l'agriculture, l'économie et l'environnement. Récemment, différents BEFMs ont été développés, souvent dans un seul but ou localisation, mais aucun de ces modèles n'a été réutilisé plus tard à d'autres fins ou lieux. Le Farm System Simulator (FSSIM) fournit un cadre générique permettant l'application de BEFMs dans différentes situations et à diverses fins (estimation des fonctions d'offre, évaluations détaillées régionale ou par type de ferme…). FSSIM est conçu comme un cadre de modélisation intégré avec des composants qui représentent les objectifs des agriculteurs, le risque, le calibrage, les politiques publiques, les activités courantes, les activités alternatives, les différentes activités de production (par exemple, les cultures annuelles et pluriannuelles et l'élevage). Le caractère générique du modèle FSSIM est évalué selon cinq critères en examinant ses applications. FSSIM a été appliqué à diverses zones pédoclimatiques (critère 1) et à plusieurs types d'exploitations (critère 2) avec différentes spécialisations, intensités et tailles. Dans la plupart des applications FSSIM a été utilisé pour évaluer les effets des changements des politiques et dans deux applications pour évaluer l'impact des innovations technologiques (critère 3). Dans les différentes applications, plusieurs sources de données, niveau de détail (par exemple, le critère 4) et configurations du modèle ont été utilisés. FSSIM a été couplé à un modèle économique et à plusieurs modèles biophysiques (critère 5). Le modèle est disponible pour des applications à d'autres conditions et enjeux de la recherche, et il est ouvert à de nouveaux essais et à être étendue avec de nouveaux composants, indicateurs ou liens vers d'autres modèles.

International audience ; Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models. ; Les modèles bioéconomiques de ferme sont des outils pour évaluer ex-post ou anticiper ex-ante l'impact des changements des politiques et des technologies sur l'agriculture, l'économie et l'environnement. Récemment, différents BEFMs ont été développés, souvent dans un seul but ou localisation, mais aucun de ces modèles n'a été réutilisé plus tard à d'autres fins ou lieux. Le Farm System Simulator (FSSIM) fournit un cadre générique permettant l'application de BEFMs dans différentes situations et à diverses fins (estimation des fonctions d'offre, évaluations détaillées régionale ou par type de ferme…). FSSIM est conçu comme un cadre de modélisation intégré avec des composants qui représentent les objectifs des agriculteurs, le risque, le calibrage, les politiques publiques, les activités courantes, les activités alternatives, les différentes activités de production (par exemple, les cultures annuelles et pluriannuelles et l'élevage). Le caractère générique du modèle FSSIM est évalué selon cinq critères en examinant ses applications. FSSIM a été appliqué à diverses zones pédoclimatiques (critère 1) et à plusieurs types d'exploitations (critère 2) avec différentes spécialisations, intensités et tailles. Dans la plupart des applications FSSIM a été utilisé pour évaluer les effets des changements des politiques et dans deux applications pour évaluer l'impact des innovations technologiques (critère 3). Dans les différentes applications, plusieurs sources de données, niveau de détail (par exemple, le critère 4) et configurations du modèle ont été utilisés. FSSIM a été couplé à un modèle économique et à plusieurs modèles biophysiques (critère 5). Le modèle est disponible pour des applications à d'autres conditions et enjeux de la recherche, et il est ouvert à de nouveaux essais et à être étendue avec de nouveaux composants, indicateurs ou liens vers d'autres modèles.